Addressing the Gap: Microeconometrics of Health Inequalities Training Course

Introduction

Despite significant advancements in healthcare and public health, persistent and often widening disparities in health outcomes remain a critical challenge across societies. These health inequalities, rooted in socio-economic status, race, gender, geographic location, and other demographic factors, represent profound inequities that demand rigorous analytical scrutiny. Microeconometrics provides the essential tools to dissect these complex relationships at the individual or household level, moving beyond aggregate statistics to identify the specific mechanisms and causal pathways through which inequalities manifest and persist.

This intensive training course is meticulously designed to equip participants with a comprehensive and practical understanding of applying microeconometric methods to analyze health inequalities. From mastering techniques to identify and measure health disparities to employing advanced causal inference strategies for understanding their determinants and evaluating policy interventions, you will gain the expertise to conduct impactful research and inform equitable health policies. This empowers you to uncover the drivers of health disparities, assess the effectiveness of programs aimed at reducing them, and contribute to building more inclusive and healthier communities.

Target Audience

  • Health economists and researchers focused on health equity.
  • Public health professionals and epidemiologists interested in social determinants of health.
  • Data analysts and statisticians working with individual-level health data.
  • Policy analysts and advisors in government agencies and healthcare organizations.
  • Academics and graduate students (Master's and PhD) in economics, public health, demography, or sociology.
  • Professionals from NGOs and international organizations engaged in health inequality reduction.
  • Social scientists investigating the socio-economic determinants of health.
  • Anyone involved in designing, monitoring, or evaluating programs aimed at reducing health disparities.

Duration: 10 days

Course Objectives

Upon completion of this training course, participants will be able to:

  • Understand the conceptual definitions of health inequality, health disparity, and health inequity.
  • Grasp various methods for measuring health inequalities using individual-level data.
  • Analyze the socio-economic, demographic, and behavioral determinants of health disparities using microeconometric models.
  • Comprehend advanced econometric techniques for establishing causal links between social factors and health outcomes.
  • Evaluate the impact of health policies and interventions on reducing health inequalities.
  • Develop practical skills in applying microeconometric methods to real-world health survey and administrative data.
  • Navigate challenges related to data quality, measurement of health, and confounding factors in inequality research.
  • Formulate evidence-based recommendations for policies and programs aimed at addressing health inequities.

Course Content

  1. Foundations of Health Inequalities: Concepts and Measurement
  • Defining health inequality, health disparity, and health inequity
  • Social determinants of health: income, education, race/ethnicity, gender, geography, social class
  • Measuring health outcomes: self-reported health, objective health measures, mortality, morbidity
  • Measures of health inequality: concentration index, slope index of inequality (SII), relative index of inequality (RII), Gini coefficient for health
  • Decomposing health inequalities: identifying contributing factors
  1. Data Sources and Management for Microeconometrics of Health
  • Common health survey datasets (e.g., DHS, LSMS, nationally representative health surveys)
  • Administrative health data (claims data, electronic health records) and their limitations
  • Linking individual-level data with contextual (e.g., neighborhood) data
  • Data cleaning, missing data handling, and variable construction
  • Ethical considerations and data privacy in sensitive health research
  1. Basic Microeconometric Models for Health Outcomes
  • Review of linear regression for continuous health outcomes
  • Binary choice models (Logit, Probit) for discrete health outcomes (e.g., self-assessed health status, presence of chronic disease)
  • Interpreting odds ratios, marginal effects, and predicted probabilities in health contexts
  • Count data models (Poisson, Negative Binomial) for healthcare utilization (e.g., number of doctor visits, hospitalizations)
  • Censored and truncated regression models (Tobit) for healthcare expenditures
  1. Endogeneity and Causal Inference in Health Inequalities
  • The challenge of establishing causality: omitted variable bias, reverse causality, simultaneity
  • Selection bias in health behaviors and healthcare utilization
  • Introduction to instrumental variables (IV) estimation for endogenous covariates
  • Understanding different sources of endogeneity in health inequality research
  • The importance of identifying credible exogenous variation
  1. Panel Data Methods for Dynamic Health Processes
  • Advantages of panel data for studying health dynamics and individual trajectories
  • Fixed Effects (FE) and Random Effects (RE) models for health outcomes
  • Dynamic panel models: accounting for persistence in health status (e.g., ARDL, GMM estimators)
  • Modeling health transitions and health shocks
  • Applications in understanding long-term impacts of early life conditions on adult health
  1. Quasi-Experimental Designs in Health Inequality Research
  • Difference-in-Differences (DiD) for evaluating policy impacts on health disparities
  • Regression Discontinuity Design (RDD) for policies with eligibility cutoffs
  • Interrupted Time Series (ITS) analysis for policy changes over time
  • Synthetic Control Method for evaluating interventions in single units
  • Applications in assessing the equity impact of health insurance reforms, public health campaigns
  1. Modeling Health Behaviors and Lifestyle Choices
  • Economic models of health behavior (e.g., Grossman model, health capital)
  • Rational addiction models and their implications for substance abuse
  • Modeling demand for healthcare services and preventive care
  • Impact of prices, income, education, and social networks on health behaviors
  • Discrete choice models for health-related decisions (e.g., smoking cessation, diet choices)
  1. Decomposing and Explaining Health Inequalities
  • Oaxaca-Blinder decomposition: attributing differences in average health outcomes to characteristics vs. coefficients
  • Decomposition of health inequality indices (e.g., concentration index decomposition)
  • Understanding the relative contributions of socio-economic factors to observed health disparities
  • Counterfactual analysis in inequality decomposition
  • Policy implications of decomposition results: targeting specific drivers of inequality
  1. Advanced Topics and Emerging Issues
  • Multilevel models for health inequalities: individual and contextual factors
  • Spatial econometrics in health: geographical disparities, neighborhood effects
  • Machine learning applications in identifying vulnerable populations and predicting health risks
  • Intersectional analysis of health inequalities (e.g., race and gender interactions)
  • The economics of mental health disparities
  • Data visualization techniques for communicating health inequalities
  1. Policy Implications and Ethical Considerations
  • Translating econometric findings into actionable health policy recommendations
  • Designing equitable health interventions and financing mechanisms
  • Ethical considerations in health inequalities research: privacy, stigmatization, research integrity
  • The role of evidence in advocacy for health equity
  • Future research directions in the microeconometrics of health inequalities.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

Addressing The Gap: Microeconometrics Of Health Inequalities Training Course in Kenya
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